Traditional molecular modeling is performed at atomic resolution, which relies on X-ray and NMR experiments to provide structural information. When dealing with biomolecular assemblies of millions of atoms, atomic description of molecular objects becomes very computational intractable. We developed a method that uses map objects for molecular modeling to efficiently derive structural information from experimental maps, as well as conveniently manipulate map objects, perform conformational search directly using map objects. This development work has been implemented into CHARMM as the EMAP module. This implementation enables CHARMM to manipulate map objects, including map input, output, comparison, docking, etc. Other experiments such as transition metal ion FRET (tmFRET) are becoming a useful way to obtain protein structure information. A new focus of our research is to combine efficient simulation technique with structural information from experiment to assist high throughput protein structure determination. Structure determination from low resolution EM maps. We developed a map-restrained self-guided Langevin dynamics (MapSGLD) simulation method for efficient targeted conformational search. The targeted conformational search represents simulations under restraints defined by experimental observations and/or by user specified structural requirements. Through map-restraints, this method provides an efficient way to maintain substructures and to set structure targets during conformational searching. With the enhanced conformational searching ability of self-guided Langevin dynamics, this approach is suitable for simulating large-scale conformational changes, such as the formation of macromolecular assemblies and transitions between vastly different conformational states. A direct application of this method is to determine macromolecular structures by flexible fitting of atomic structures into density maps derived from cryo-electron microscopy. Conformational study of Thermosome. Collaborated with Prof. George Stan at University of Cincinnati, the conformational states of Thermosome was studied with the map constrained simulation method. The open state conformation was obtained through self-guided molecular dynamics simulation combined with the map constrained simulation method. The simulation results provide insight to the functional pathway of theromsome. It also demonstrate the powerful capability of the map constrained simulation method in bridging the experimental map information to structural and dynamic studies. Molecular modeling and simulation of the gp140/sugar system. Colaboration with Dr. Sriram Subramaniam at NCI we performed a molecular modeling and simulation study of gp140/sugar system. GP140 is homology modeled mainly based PDB structure, 3jwd. The v1v2 loop region was modeled based on a remote homologeous PDB structure 1ciy. The V3 loop was modeled based on PDB structure, 2b4c. Glycan molecules were docked on the gp140 surface using the EMAP module1 of CHARMM2. The gp140-sugar system was fit into the EM map determined from their lab with the EMAP module1 of CHARMM2 to produce the trimer system. The N- and C- terminal motifs of the trimer are fixed by assuming they binding to gp41. The rest part of the trimer is simulated using the self-guided langevin dynamics (SGLD) simulation method to promote conformational changes. In a 1 ns SGLD simulation, we observed the conformation changed from initial closed state to a open state that is similar to the structure, 3DNO. Molecular basis of Chemotaxi. In chemotaxic bacteria, transmembrane chemoreceptors, CheA and CheW form the core signaling complex of the chemotaxis sensory apparatus. These complexes are organized in extended arrays in the cytoplasmic membrane that allow bacteria to respond to changes in concentration of extracellular ligands via a cooperative, allosteric response that leads to substantial amplification of the signal induced by ligand binding. Here, we have combined cryo-electron tomography studies of the 3D spatial architecture of chemoreceptor arrays in intact E. coli cells with computational modeling to develop a predictive model for the cooperativity and sensitivity of the chemotaxis response. The predictions were tested experimentally using fluorescence resonance energy transfer (FRET) microscopy. Our results demonstrate that changes in lateral packing densities of the partially ordered, spatially extended chemoreceptor arrays can modulate the bacterial chemotaxis response, and that information about the molecular organization of the arrays derived by cryo-electron tomography of intact cells can be translated into testable, predictive computational models of the chemotaxis response. Accurate High-Throughput Structure Mapping and Prediction with Transition Metal Ion FRET. Mapping the landscape of a protein's conformational space is essential to understanding its functions and regulation. The limitations of many structural methods have made this process challenging for most proteins. We collaborated with Dr. Justin Taraska of NHLBI to use transition metal ion FRET (tmFRET) in a rapid, highly parallel screen, to determine distances from multiple locations within a protein at extremely low concentrations. The distances generated through this screen for the protein maltose binding protein (MBP) match distances from the crystal structure to within a few angstroms. Applying SGLDfp simulations with FRET distance restrains, we can quickly determine the structures at corresponding states. Our results open the door to rapid, accurate mapping and prediction of protein structures at low concentrations, in large complex systems, and in living cells. Protein complex structures prediction. Proteinprotein interactions, defined as specific physical contacts between protein pairs that occur by selective molecular docking in a particular biological context, are critical to many biological functions such as signal transduction and immune response and are therapeutic drug targets. Hence, a detailed understanding of the mechanisms of protein association is of wide interest and of importance for drug design. Knowledge of the 3-dimensional (3D) structure of the proteinprotein complex is prerequisite for understanding how proteins associate. However, experimental determination of these proteinprotein complex structures by X-ray, NMR, and cyroelectron microscopy is time-consuming and is limited by the size of the complex. Thus, in silico proteinprotein docking approaches, which can predict the complex structure from the coordinates of the unbound component proteins, complement experimentally determined protein complex structures. The EMAP method implemented in the CHARMM program provides an efficient tool to perform protein-protein docking. Further development of EMAP will focus on the energy function to more accurately recognize native complexes. Atomic mechanism of the kinesin walking on microtubule. Kinesin is a protein belonging to the class of cytoskeletal motor proteins. Kinesin converts the energy of ATP hydrolysis into stepping movement along microtubules, which supports several vital cellular functions including mitosis, meiosis, and the transport of cellular cargo. Because kinesin is a fundamental protein, further research on the topic will provide important information as to how it functions. Combined with low resolution electron microscopic images, self-guided Langevin dynamics simulations are performed to study molecular motion and conformational change of kinesin motor domain in water and binding with microtubule. SGLD enable simulation to reach the time scale required for conformational change to understand the role of ATP binding and interaction with microtubules.